GCP Data Engineer

Role Name: GCP Data Engineer

Work Location: Toronto, Canada (Remote)

Job Summary

We are seeking an experienced GCP Data Engineer with hands-on expertise in Google Cloud Platform (GCP), particularly BigQuery, and familiarity with DBT for data transformation and modeling. The ideal candidate will have strong SQL skills, a solid understanding of data warehousing concepts, and basic to intermediate Python skills for scripting and automation. Experience working with large-scale operational and customer interaction datasets is preferred.

Key Responsibilities

• Design, build, and maintain scalable data pipelines using GCP services, primarily BigQuery.
• Develop and manage DBT models to transform raw data into clean, tested, and documented datasets.
• Write complex, optimized SQL queries for data extraction, transformation, and analysis.
• Implement and maintain data warehousing solutions, ensuring performance, scalability, and reliability.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver high-quality data solutions.
• Monitor and troubleshoot data pipeline performance and data quality issues.
• Automate data workflows and tasks using Python scripts where required.
• Follow data governance, security, and compliance best practices.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent experience.
• At least 5 years of experience in data engineering or a similar role.
• Strong SQL skills, including the ability to write complex and efficient queries.
• Hands-on experience with BigQuery and other GCP data services.
• Familiarity with DBT for data transformation and modeling.
• Solid understanding of data warehousing principles and best practices.
• Basic to intermediate Python skills for scripting and automation.
• Familiarity with version control systems such as Git.
• Strong problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience working with large-scale operational, customer interaction, or network-related datasets.
• Exposure to data transformation, modeling, and workflow automation best practices.